Network Analysis of World Cities/Global Service Firms Data: an Exploratory Investigation

This is a pilot project conducted as part of Ben Derudder’s study leave from the University of Ghent spent at the Department of Geography, Loughborough University (October-November 2002).

In project 10, a large-scale data collection exercise was undertaken that produced a matrix covering 315 cities and 100 global service firms. Each cell contains a ‘service value’ on a scale from zero to five that indicates how important City X is to Firm Y’s global strategy for office location (City X scoring 0 means that Firm Y has no presence in the city, City X scoring 5 indicates that it houses Firm Y’s headquarters). For details see Taylor et al. 2002a.

This data has been analysed using principal components analyses (Taylor et al. 2002b) and Taylor et al. forthcoming) and fuzzy set analyses (Derudder and Witlox 2002; Derudder et al. 2002a and b). These techniques have explored the structure in the data but they do not directly analyse connections between cities. The latter has been carried out as a measurement exercise to derive the ‘global network connectivities’ of cities (Taylor et al. 2002a and c) but no further ‘network analyses’ have been undertaken for this data. This is despite the fact that in the original specification of the world city network (Taylor 2001), inter-city relational matrices were defined.

One reason for the lack of use of network analysis with the Project 10 data is that the basic techniques generally use a simple 0/1 matrix of connections (objects are either linked or not linked) whereas the inter-city matrices produced from our specification and data creates ratio measures of connectivity. Converting the latter to integers requires using a threshold defining above as I and below as 0. Although we lose much information by such simple dichotomising, it does open up a new experimental design possibility through varying the threshold and comparing the different network results that are produced. It is this approach to network analysis of world cities that is explored in this project.

The software package we will use is UCINET; as with many other analyses we focus on just the top 123 world cities (defined by their connectivities); and we expect to be able to identify ‘cliquishness’ amongst world cities.

References

Derudder, B and Witlox, F (2002) ‘Fuzzy classifications of large geographical databases: towards an assessment of the network of world cities’, GaWC Research Bulletin No. 75